Authors:
Mariam Mubarak
1
;
Kamran Khalid
1
;
Fizza Waqar
2
;
Ali Tahir
1
;
Ibraheem Haneef
3
;
Gavin McArdle
4
and
Michela Bertolotto
4
Affiliations:
1
Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad, Pakistan
;
2
GIS Plus Total Solutions, Islamabad, Pakistan
;
3
Dept. of Mech & Aerospace Engg, Air University, Islamabad, Pakistan
;
4
School of Computer Science, University College Dublin, Dublin 4, Ireland
Keyword(s):
Real Estate, Map Personalisation, Map Recommendation, Implicit Profiling, Estatech Maps, Real Estate Analytics.
Abstract:
The value of global real estate was $217 trillion in 2015 which is 2.7 times world GDP, making up roughly 60% of mainstream global assets and consequently it is considered one of the main drivers of economic growth. The availability of geospatial big data can assist real estate stakeholders to make informed decisions and increase their profits. Location plays a significant role in real estate decision making and so maps represent an excellent resource for real estate planning. Personalisation can assist with real estate decisions by ascertaining a user’s interests and preferences which can be captured via interaction with maps. A personalised real estate portal can then use this information to recommend properties on the web aiding property buyers and provide valuable real estate analytics. In this paper, we propose an approach for a personalised real estate platform called Estatech Maps. This will be a pioneer in the real estate industry, the key focus of which is to alter the preva
iling management practices by imparting GIS and data analytics as long-term solutions.
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